Date: Wednesday , October 12, 2016
Data generated by machines & devices, cloud-based solutions and business management, has reached a total volume of more than 1000 Exabytes annually and is expected to increase twenty-fold in the next ten years. On the other hand, analytical apps (which also leverage technologies such as IoT) are witnessing increasing hybridization, where intelligence is being added to existing transaction processes and systems. Born in 2015 as the brain child of financial services & technology industry veterans, Pentation Analytics has mastered the art of enabling organizations to productively use this voluminous data to grow their business. The company was incepted with the objective of combining the promoters\' extensive business experience with emerging data science & big data technologies, for offering analytic applications for enterprise customers.

\"At Pentation Analytics, the effort to understand business processes at enterprises and capacity building on technical know-how is an on-going process,\" reveals Anirban Roy, CEO, Pentation Analytics. Standing by this philosophy has not only facilitated this Mumbai headquartered company to garner an impressive turnover and marquee clientele, but has also enriched its portfolio with awards such as \'Top Analytics Company by CIO Magazine\' and certifications like from NASSCOM & ISMS ISO 27001, which are on display as a testimony to its dedication and efficiency.

A Rare Gem in the Saturated Market

While the technologies being used to deliver analytics solutions have been changing rapidly, enterprises are still exploring opportunity areas where analytics can add value. Grounding its engagement phase in this reality, the company lays great emphasis on client interaction and sheds spotlight on business problem areas during implementation. Although the Insurance technology space is saturated with increasing number of solution providers, many of these solutions focus on one or two aspects of the Insurance industry value chain. Pentation Analytics surges ahead of the competition with its aspirations and capability to develop analytics products & services across the Insurance and BFSI value chain. The company is focused on developing predictive analytics based Services, Solutions and Products for the Banking, Financial Services, Capital Markets, Insurance and Payments industries along with SCM and SCRM solutions to enhance the installed ERP and CRM implementations. Leveraging market leading big data technology platforms to develop the applications allow Pentation Analytics to add value to enterprises.

Customer Activation for Capital Markets

Pentation Analytics has developed a predictive analytics solution, Practive, for capital market enterprises such as Securities Broking firms and Fund Houses. The company uses predictive analytics algorithms that enable activation of existing customers through \'Practive\', using analytical records as the base data layer. \"This allows Pentation Analytics to add value to the enterprises at two levels: owing to domain experience, predictive models and applications are focused on solving current business problems and secondly, usage of big data technology allows utilization of structured and unstructured datasets and as well prepares enterprises to be future ready\", states Roger Joag, Sr. VP of Product Engineering and Head-International Business, Pentation Analytics.

Enabling Clients to Exploit the \'Big\' Opportunities in Disguise

Aside from its unique capability of providing time and size scalable Clusters for Customers (which are real-time data i/o friendly), Pentation Analytics stands apart with the unique advantage of skill, expertise and experience in all the four major stack layers that are a part of this challenge and ecosystem - The Data Hardware, the Platform, the Statistical/Analytical/Language/Service Layer and the Visualization layer. These Crucial four layer capability of design, configure and deploy of the Data File Systems, the Platform tools (either open-source or traditional) and the Predictive & Prescriptive IP based Analytics layer crowned by the Business Intelligence layer has enabled Pentation Analytics to help its customers excel in exploiting the big data challenge (of ever-increasing data volume) to move ahead of their competition, rather than be stifled by it.

Delinquency Prediction Model for Loans

Lenders worldwide, ranging from Payment Houses, Banks, Home and Commercial Real Estate Brokers, Educational lenders, etc., have witnessed rising delinquency rates. While delinquency of large borrowers often ends up on the negotiation table, solution for addressing potential delinquency situations for the consolidators and buyers in the retail scenario lie in appropriate data driven decisions. Pentation Analytics\' predictive models for Loans, both for Performing and Non-Performing Loans, are developed on sectorial trends. Specifically for Non-Performing Loans, the ideal pricing for the sellers, the consolidators and buyers, hinges on recovery estimation and delinquency behavioral models. The model developed at Pentation Analytics utilizes data from loan pools for recovery estimation and tail value calculation rather than one single loan book.

Now that the company is fully entrenched and tremendously successful in India, it envisions expanding to cover world geography. As the data juggernaut is only set to grow in geometric proportions, Pentation Analytics, leveraging its unique expertise in the scalable architecture and model, is emerging into a force to be reckoned with.

Key Management

Anirban Roy, CEOThis IIM-Lucknow alumnus with 18+ years of experience in BFSI, IT, consumer, media & entrepreneurship spearheads Pentation Analytics on the Company Board as well.

Exceptional Skill:Pentation Analytics has deployed its proprietary capital market analytical record solution for a reputed securities market brokerage houses to enable speedy analysis and business insights generation. And it developed the predictive analytics algorithms that enable activation of customers for transactions using analytical record as the base data layer.